Volume 22 Supplement 12

Explainable AI methods in biomedical data science

Research

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

Virtual24-25 January 2021

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Edited by Henry Han and XiangRong Liu.

The challenges of explainable AI in biomedical data science

Authors: Henry Han and Xiangrong Liu

Citation: BMC Bioinformatics 2022 22(Suppl 12):443

Content type: Introduction Published on: 20 January 2022
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Drug–target interaction prediction via multiple classification strategies

Computational prediction of the interaction between drugs and protein targets is very important for the new drug discovery, as the experimental determination of drug-target interaction (DTI) is expensive and t...

Authors: Qing Ye, Xiaolong Zhang and Xiaoli Lin

Citation: BMC Bioinformatics 2022 22(Suppl 12):461

Content type: Research Published on: 20 January 2022
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A truncated nuclear norm and graph-Laplacian regularized low-rank representation method for tumor clustering and gene selection

Clustering and feature selection act major roles in many communities. As a matrix factorization, Low-Rank Representation (LRR) has attracted lots of attentions in clustering and feature selection, but sometime...

Authors: Qi Liu

Citation: BMC Bioinformatics 2022 22(Suppl 12):436

Content type: Research Published on: 20 January 2022
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Detect the early-warning signals of diseases based on signaling pathway perturbations on a single sample

During the pathogenesisof complex diseases, a sudden health deterioration will occur as results of the cumulative effect of various internal or external factors. The prediction of an early warning signal (pre-...

Authors: Yanhao Huo, Geng Zhao, Luoshan Ruan, Peng Xu, Gang Fang, Fengyue Zhang, Zhenshen Bao and Xin Li

Citation: BMC Bioinformatics 2022 22(Suppl 12):367

Content type: Methodology Published on: 20 January 2022
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Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data

The identification of cancer types is of great significance for early diagnosis and clinical treatment of cancer. Clustering cancer samples is an important means to identify cancer types, which has been paid m...

Authors: Juan Wang, Cong-Hai Lu, Xiang-Zhen Kong, Ling-Yun Dai, Shasha Yuan and Xiaofeng Zhang

Citation: BMC Bioinformatics 2022 22(Suppl 12):334

Content type: Research Published on: 20 January 2022
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Predicting Ca²⁺ and Mg²⁺ ligand binding sites by deep neural network algorithm

Alkaline earth metal ions are important protein binding ligands in human body, and it is of great significance to predict their binding residues.

Authors: Kai Sun, Xiuzhen Hu, Zhenxing Feng, Hongbin Wang, Haotian Lv, Ziyang Wang, Gaimei Zhang, Shuang Xu and Xiaoxiao You

Citation: BMC Bioinformatics 2022 22(Suppl 12):324

Content type: Research Published on: 20 January 2022
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Identifying biomarkers for breast cancer by gene regulatory network rewiring

Mining gene regulatory network (GRN) is an important avenue for addressing cancer mechanism. Mutations in cancer genome perturb GRN and cause a rewiring in an orchestrated network. Hence, the exploration of ge...

Authors: Yijuan Wang and Zhi-Ping Liu

Citation: BMC Bioinformatics 2022 22(Suppl 12):308

Content type: Methodology Published on: 20 January 2022
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MetaCRS: unsupervised clustering of contigs with the recursive strategy of reducing metagenomic dataset’s complexity

Metagenomics technology can directly extract microbial genetic material from the environmental samples to obtain their sequencing reads, which can be further assembled into contigs through assembly tools. Clus...

Authors: Zhongjun Jiang, Xiaobo Li and Lijun Guo

Citation: BMC Bioinformatics 2022 22(Suppl 12):315

Content type: Methodology Published on: 20 January 2022
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DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph

Long non-coding RNAs (lncRNAs) play a crucial role in diverse biological processes and have been confirmed to be concerned with various diseases. Largely uncharacterized of the physiological role and functions...

Authors: Long Yang, Li-Ping Li and Hai-Cheng Yi

Citation: BMC Bioinformatics 2022 22(Suppl 12):621

Content type: Review Published on: 25 February 2022
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Using entropy-driven amplifier circuit response to build nonlinear model under the influence of Lévy jump

Bioinformatics is a subject produced by the combination of life science and computer science. It mainly uses computer technology to study the laws of biological systems. The design and realization of DNA circu...

Authors: Hao Fu, Hui Lv and Qiang Zhang

Citation: BMC Bioinformatics 2022 22(Suppl 12):437

Content type: Research Published on: 20 January 2022
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Explainable AI methods in biomedical data science

Research

The challenges of explainable AI in biomedical data science

Drug–target interaction prediction via multiple classification strategies

A truncated nuclear norm and graph-Laplacian regularized low-rank representation method for tumor clustering and gene selection

Detect the early-warning signals of diseases based on signaling pathway perturbations on a single sample

Multi-view manifold regularized compact low-rank representation for cancer samples clustering on multi-omics data

Predicting Ca²⁺ and Mg²⁺ ligand binding sites by deep neural network algorithm

Identifying biomarkers for breast cancer by gene regulatory network rewiring

MetaCRS: unsupervised clustering of contigs with the recursive strategy of reducing metagenomic dataset’s complexity

DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph

Using entropy-driven amplifier circuit response to build nonlinear model under the influence of Lévy jump

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